Devices which rely on machine vision such as robotic and manufacturing equipment, image based measurement equipment, topographical mapping equipment, and image recognition systems often use correlation of a single image (auto-correlation) or correlation between multiple images (cross-correlation) to establish the size, shape, speed, acceleration and/or position of one or more objects within a field of view.
Particle image velocimetry (PIV) uses autocorrelation or cross-correlation to analyze flow characteristics in fluids. PIV is a flow measurement technique that provides quantitative, two-dimensional information of a flow velocity field. For general background information regarding PIV, see Adrian, R. J., "Particle Imaging Techniques For Experimental Fluid Mechanics", Annual Review of Fluid Mechanics, vol. 23, pp. 261-304 (1991). Unlike more traditional instruments such as hot-wire and laser-Doppler anemometery which are single-point measurement techniques, PIV is able to reveal the instantaneous spatial structures in a flow. Because of the high-resolution of information that can be obtained by PIV, determination of flow quantities such as vorticity and deformation are obtainable.
Until recently, PIV has been limited to applications in which two-dimensional, instantaneous velocity measurements are of interest. Holographic Particle Image Velocimetry (HPIV) and Stereoscopic PIV (SPIV) are being developed for quantitatively measuring three-dimensional flow velocity fields and for resolving unsteady flow structures. The usefulness of these techniques, however, is hindered by the present ability to analyze the enormous quantities of data in a reasonable time period.
Image correlation is typically performed using Fast Fourier Transforms (FFTs), image shifting, or optical transformation techniques. These techniques, although accurate, require extensive processing of the images in hardware or software. For an image having N.times.N pixels, for example, FFT techniques require on the order of N.sup.2 log N iterations while image shifting techniques require .DELTA..sup.2 N.sup.2 iterations, where .DELTA. is the length of the correlation search in pixels. With either of these techniques, the image or a subsection of the image is fully (i.e. 100%) correlated regardless of the usefulness of the information content.
The optical transformation technique relies on the optical construction of the Young's fringes formed when a coherent light is passed through the image and then through Fourier transform optics. The resulting fringe pattern is digitized and analyzed by a computer. This is certainly the most elegant of the three methods and potentially the fastest. In practice, however, it has been found that it is difficult to detect the orientation of the Young's fringes.